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I work in machine learning. I regularly get jazzed when I figured out a linear solution to a problem (e.g., using a min heap to grab top k elements from a similarity computation in a recommendation system instead of first sorting), and will remark on such to anyone I'm working with. In more mundane settings, I'll also regularly use, say, hash tables to store data for convenient constant time lookup instead of naively scanning through a list each time I need to find an index.

I think I can safely say that asymptotic time and space concerns of a problem firmly guide much of my choices in data structure and algorithm use. Though this is maybe followed closely by aesthetic pleasure, novelty of trying something new and neat, or clarity in the functional organization/readability/maintainability of the code.

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